Atmospheric optical turbulence prediction method and device

Abstract

The application provides an atmospheric optical turbulence prediction method and device, the method comprising: obtaining meteorological data at a first time and atmospheric coherence length data within a first time period; inputting the meteorological data into a target model to obtain a preliminary turbulence prediction result; extracting a time feature of the atmospheric coherence length data, and updating the preliminary turbulence prediction result based on the time feature to obtain an updated turbulence prediction result. The method reduces the interference of errors caused by the dynamics and randomness of turbulence on the turbulence prediction result, and improves the accuracy of atmospheric optical turbulence prediction.

Description

Technical Field

[0001] This invention relates to the field of atmospheric optical technology, and in particular to a method and apparatus for predicting atmospheric optical turbulence. Background Technology

[0002] When the satellite-to-ground laser communication link is affected by atmospheric optical turbulence, it can easily lead to an increase in the bit error rate of the ground receiving system or cause communication interruption. Timely and accurate forecasting of atmospheric optical turbulence is of great significance for the normal operation of the ground receiving system.

[0003] In related technologies, numerical weather prediction is commonly used to forecast turbulence. However, the turbulence profiles used in numerical weather prediction methods are statistical summaries of some observatories, which have regional characteristics. This means that the profiles cannot accurately describe the turbulence patterns at new stations, leading to inaccurate forecasts. Furthermore, the ability of statistical methods to characterize the relationship between atmospheric refractive index structure constants and meteorological factors is also limited. There are significant errors between the meteorological factors used to calculate turbulence forecasts and the actual measured meteorological parameters. For example, the error range for factors such as wind direction can reach 200%, resulting in inaccurate final turbulence forecasts. Summary of the Invention

[0004] This invention provides an atmospheric optical turbulence forecasting method and apparatus to address the limitations of existing technologies in obtaining numerical weather predictions, which are restricted by environmental factors such as specific geographical location, topography, solar altitude angle, and season, resulting in limited accuracy of numerical weather predictions. Furthermore, the invention addresses the shortcomings of existing technologies in characterizing the relationship between atmospheric refractive index structure constant and meteorological factors, leading to low accuracy in forecasting atmospheric optical turbulence. This invention improves the accuracy of atmospheric optical turbulence forecasting results.

[0005] This invention provides a method for predicting atmospheric optical turbulence, comprising:

[0006] Acquire meteorological data at the first moment and atmospheric coherence length data within the first time period;

[0007] The meteorological data is input into the target model to obtain preliminary turbulence forecast results. The target model is used to predict the turbulence intensity of the meteorological data.

[0008] The temporal features of the atmospheric coherence length data are extracted, and the preliminary turbulence forecast results are updated based on the temporal features to obtain the updated turbulence forecast results. The temporal features are used to represent the amount of change of the atmospheric coherence length data within the target number of days.

[0009] According to the atmospheric optical turbulence forecasting method provided by the present invention, the meteorological data includes multiple meteorological factors, the target model includes a first formula and a turbulence profile, the turbulence profile is used to represent the variation characteristics of turbulence with altitude, and the step of inputting the meteorological data into the target model to obtain preliminary turbulence forecasting results includes:

[0010] Based on the first formula, the atmospheric refractive index structure constants corresponding to the multiple meteorological factors at different layer heights are obtained;

[0011] The atmospheric refractive index structure constants of the multiple meteorological factors at different layer heights are integrated according to the turbulence profile to obtain the preliminary turbulence forecast results.

[0012] According to the atmospheric optical turbulence forecasting method provided by the present invention, the meteorological data includes multiple meteorological factors, the target model includes a first formula and a turbulence profile, the turbulence profile is used to represent the variation characteristics of turbulence with altitude, and the step of inputting the meteorological data into the target model to obtain preliminary turbulence forecasting results further includes:

[0013] Acquire target atmospheric coherence length data based on differential image motion monitoring equipment;

[0014] Environmental features and temporal variation features are extracted from the target atmospheric coherence length data, and the turbulence profile is updated based on the environmental features and the temporal variation features;

[0015] The atmospheric refractive index structure constants corresponding to the multiple meteorological factors at different layer heights are integrated according to the updated turbulence profile to obtain the turbulence forecast result. The atmospheric refractive index structure constants are obtained based on the first formula.

[0016] According to an atmospheric optical turbulence prediction method provided by the present invention, after updating the preliminary turbulence prediction result based on the time characteristics, the method further includes:

[0017] Receive satellite orbit information sent by an external system. The satellite orbit information includes multiple azimuth and elevation angles of the satellite in its orbit. Each of the multiple azimuth and elevation angles corresponds to a different updated turbulence prediction result.

[0018] Based on the satellite orbit information, the target turbulence prediction results corresponding to the multiple azimuth and elevation angles and the comprehensive turbulence prediction results corresponding to the satellite orbit are obtained;

[0019] The target turbulence prediction results corresponding to the multiple azimuth and elevation angles and the comprehensive turbulence prediction results are sent to the external system.

[0020] According to the atmospheric optical turbulence prediction method provided by the present invention, the first formula is:

[0021]

[0022] in, Let be the atmospheric refractive index structure constant, a be a constant, L0 be the turbulent external scale, and M be the potential refractive index gradient.

[0023] This invention provides an atmospheric optical turbulence prediction device, comprising:

[0024] The acquisition module is used to acquire meteorological data at the first moment and atmospheric coherence length data within the first time period;

[0025] The first processing module is used to input the meteorological data into the target model to obtain preliminary turbulence forecast results, and the target model is used to predict the turbulence intensity of the meteorological data.

[0026] The second processing module is used to extract the temporal features of the atmospheric coherence length data and update the preliminary turbulence forecast result based on the temporal features to obtain the updated turbulence forecast result. The temporal features are used to represent the amount of change of the atmospheric coherence length data within the target number of days.

[0027] An atmospheric optical turbulence prediction device according to the present invention further includes:

[0028] The receiving module is used to receive satellite orbit information sent by an external system. The satellite orbit information includes multiple azimuth and elevation angles of the satellite in its orbit, and the multiple azimuth and elevation angles correspond to different updated turbulence prediction results.

[0029] The third processing module is used to obtain the target turbulence prediction results corresponding to the multiple azimuth and elevation angles and the comprehensive turbulence prediction results corresponding to the satellite orbit based on the satellite orbit information;

[0030] The sending module is used to send the target turbulence prediction results corresponding to the multiple azimuth and pitch angles and the comprehensive turbulence prediction results to the external system.

[0031] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the atmospheric optical turbulence prediction method as described above.

[0032] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the atmospheric optical turbulence prediction method as described above.

[0033] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the atmospheric optical turbulence prediction method as described above.

[0034] The atmospheric optical turbulence forecasting method and apparatus provided by this invention calculates the turbulence forecasting results for future times by acquiring meteorological data at future times, and extracts the temporal characteristics of atmospheric coherence length data collected in real time. Then, the temporal characteristics are used to update the turbulence forecasting results for future times, thereby reducing the interference of errors caused by the dynamic and random nature of turbulence on the turbulence forecasting results and improving the accuracy of atmospheric optical turbulence forecasting. Attached Figure Description

[0035] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0036] Figure 1 This is one of the flowcharts of the atmospheric optical turbulence prediction method provided by the present invention;

[0037] Figure 2 This is the second schematic diagram of the atmospheric optical turbulence prediction method provided by the present invention;

[0038] Figure 3 This is one of the structural schematic diagrams of the atmospheric optical turbulence prediction device provided by the present invention;

[0039] Figure 4 This is the second schematic diagram of the atmospheric optical turbulence prediction device provided by the present invention;

[0040] Figure 5 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0042] The following is combined Figures 1-4 The present invention describes the atmospheric optical turbulence prediction method and apparatus.

[0043] Figure 1This is one of the flowcharts of the atmospheric optical turbulence prediction method provided by the present invention, such as... Figure 1 As shown, the atmospheric optical turbulence prediction method includes steps 110, 120 and 130.

[0044] Step 110: Obtain meteorological data at the first moment and atmospheric coherence length data within the first time period.

[0045] In this step, the first moment can be a future moment. For example, the first moment can be any moment within 24 hours of the current moment. The first time period includes multiple time points, and the atmospheric coherence length data is dynamically updated within the first time period.

[0046] In this step, meteorological data can be downloaded from the Weather Research and Forecasting Model (WRF) server, and atmospheric coherence length data can be acquired in real time by the Differential Image Motion Monitor (DIMM).

[0047] The following example illustrates how to use a WRF server to obtain meteorological data at the first moment and DIMM to collect atmospheric coherence length data at the second moment.

[0048] In this embodiment, meteorological data of the laser communication station site area (corresponding to the specified area) is first extracted from the WRF server, and the output result is a .nc file. The meteorological data is divided into three nested layers, labeled as d01, d02 and d03 respectively. The resolutions of each layer of meteorological data are 25km, 5k and 1km respectively, and the number of grid points is 100*100. The 24-hour forecast result of 100km*100km near the innermost target station site is selected, and a forecast is made every 6 hours with a forecast resolution of 10 minutes.

[0049] In this embodiment, a DIMM is first installed at the same height as the optical receiving system within the laser communication station to ensure that there are no obstructions within the DIMM's field of view, so as to conduct long-term, all-day atmospheric coherence length monitoring. After a full year of monitoring, the DIMM can automatically record the azimuth, pitch angle information and atmospheric coherence length measurement results of each observation, and convert the slant path observation results to the vertical direction perpendicular to the ground.

[0050] In this embodiment, the DIMM has a high response rate and can take the average value of every 3000 motion results collected by the DIMM as one output result, with an output interval of about 23 seconds. The measured results are automatically updated and uploaded to the subsequent processing module.

[0051] In this embodiment, meteorological data at a first moment and atmospheric coherence length data at a second moment can be acquired within a specified area. The features analyzed or extracted from the acquired atmospheric coherence length data are used to represent the changes in atmospheric optical turbulence within the specified area, and are used to correct or update the prediction deviation of turbulence information in the meteorological data acquired at the first moment.

[0052] Step 120: Input meteorological data into the target model to obtain preliminary turbulence forecast results. The target model is used to predict the turbulence intensity of the meteorological data.

[0053] In this step, the first model can be an empirical model used to calculate the atmospheric coherence length, and the atmospheric coherence length is negatively correlated with the turbulence intensity, that is, the larger the atmospheric coherence length, the weaker the turbulence.

[0054] In this embodiment, the first model may consist of an algorithm for the atmospheric refractive index structure constant and a preset turbulence profile. The preset turbulence profile can be modified according to actual environmental characteristics to improve the first model's ability to predict turbulence forecast results in meteorological data.

[0055] In this step, the turbulence forecast result is the atmospheric coherence length corresponding to the meteorological data.

[0056] In this embodiment, after calculating the meteorological factors using the atmospheric refractive index structure constant algorithm and converting them using the turbulence profile, the atmospheric coherence length corresponding to the meteorological data at the first moment can be obtained.

[0057] In this embodiment, a WRF server can be used to forecast the weather in the laser communication station area, and the atmospheric refractive index structure constants at different heights can be calculated using meteorological factors such as temperature and air pressure. Then, the atmospheric refractive index structure constants at different heights can be integrated according to the turbulence profile to obtain the turbulence forecast results.

[0058] Step 130: Extract the temporal features of the atmospheric coherence length data and update the preliminary turbulence forecast results based on the temporal features to obtain the updated turbulence forecast results. The temporal features are used to represent the amount of change in the atmospheric coherence length data within the target number of days.

[0059] It should be noted that the atmospheric refractive index structure constant may be different at different levels or at different times within the same region. For example, the atmospheric refractive index structure constants of the troposphere and stratosphere above the same region are different, and the atmospheric refractive index structure constants of different seasons, months, days or times in the same region are also different.

[0060] In this step, the time length of the target number of days can be a year, a month or several months (a quarter), or multiple moments within a week or a day.

[0061] In this step, the time characteristic can be the average value of the atmospheric refractive index structure constant at different time points or at different layer heights as the time characteristic of the atmospheric coherence length.

[0062] In this embodiment, the time feature can be one or more combinations of the mean atmospheric coherence length data in different seasons, the mean atmospheric coherence length data corresponding to different months, the mean atmospheric coherence length data corresponding to different time points within different numbers of days and units of days.

[0063] In this embodiment, the average value of atmospheric coherence length data monitored in real time by DIMM is used as the smallest unit of data analysis within 10 minutes. The atmospheric coherence length data is used as the time coefficient of atmospheric coherence length by one or more combinations of the average values ​​of different time periods in season, month, ten-day period and unit number of days. The time coefficient is substituted into the turbulence forecast results for numerical correction to obtain the updated turbulence forecast results.

[0064] The atmospheric optical turbulence forecasting method provided by this invention calculates the turbulence forecasting results for future times by acquiring meteorological data at future times, and extracts the temporal characteristics of atmospheric coherence length data collected in real time. Then, the temporal characteristics are used to update the turbulence forecasting results for future times, thereby reducing the interference of errors caused by the dynamic and random nature of turbulence on the turbulence forecasting results and improving the accuracy of atmospheric optical turbulence forecasting.

[0065] In some embodiments, meteorological data includes multiple meteorological factors, and the target model includes a first formula and a turbulence profile, wherein the turbulence profile is used to represent the variation characteristics of turbulence with height; inputting meteorological data into the target model to obtain preliminary turbulence forecast results includes: obtaining the atmospheric refractive index structure constants corresponding to multiple meteorological factors at different layer heights based on the first formula; and performing integration calculations on the atmospheric refractive index structure constants corresponding to multiple meteorological factors at different layer heights according to the turbulence profile to obtain preliminary turbulence forecast results.

[0066] In this embodiment, meteorological factors include temperature, air pressure, wind speed, wind direction, and temperature gradient.

[0067] In this embodiment, the first formula is used to calculate the atmospheric refractive index structure constant corresponding to different layer heights of meteorological factors within the atmosphere, so as to obtain the atmospheric coherence length corresponding to the meteorological data.

[0068] In this embodiment, the turbulence profile can be preset profile data in an empirical model, or it can be profile data optimized according to the environmental characteristics corresponding to different regions.

[0069] Figure 2 This is the second schematic diagram of the atmospheric optical turbulence prediction method provided by the present invention. Figure 2 In the embodiment shown, the WRF server downloads the meteorological data at the first moment, and after preprocessing the meteorological data, extracts multiple meteorological factors. Each meteorological factor is automatically reported to the preliminary calculation unit at regular intervals. That is, the atmospheric refractive index structure constant corresponding to each meteorological factor is calculated by the first formula corresponding to the target model, and the atmospheric refractive index structure constant is integrated according to the preset turbulence profile to obtain the preliminary turbulence forecast result corresponding to the meteorological data.

[0070] The atmospheric optical turbulence forecasting method provided by this invention obtains the predicted values ​​of atmospheric coherence lengths corresponding to multiple meteorological factors through a first formula and turbulence profile, realizing real-time monitoring of turbulence forecasting results in the meteorological data, and also providing input data for subsequent correction of the forecasting results.

[0071] In some embodiments, the meteorological data includes multiple meteorological factors, and the target model includes a first formula and a turbulence profile, the turbulence profile being used to represent the variation characteristics of turbulence with height; inputting the meteorological data into the target model to obtain preliminary turbulence forecast results, further includes: acquiring target atmospheric coherence length data based on differential image motion monitoring equipment; extracting environmental features and temporal variation features from the target atmospheric coherence length data, and updating the turbulence profile based on the environmental features and temporal variation features; integrating the atmospheric refractive index structure constants of multiple meteorological factors at different layer heights according to the updated turbulence profile to obtain turbulence forecast results, the atmospheric refractive index structure constants being obtained based on the first formula.

[0072] It is understandable that when obtaining turbulence information from meteorological data, the atmospheric refractive index structure constant corresponding to each meteorological factor is first calculated using the first formula. Then, the atmospheric refractive index structure constant is integrated according to the preset turbulence profile to obtain the atmospheric coherence length, which can be used to represent the predicted value of turbulence intensity in meteorological data. The accuracy of the turbulence profile affects the accuracy of the predicted value of turbulence intensity.

[0073] In this embodiment, environmental features can be the natural geographical features of a designated area, climatic features, or a combination of geographical and climatic features.

[0074] In this embodiment, in order to improve the accuracy of the corresponding profiles of various meteorological factors under different environmental conditions (different geographical conditions or different climatic conditions), a new turbulence profile that conforms to the local geographical conditions and climatic characteristics can be fitted by measurement within a specified area, so as to improve the accuracy of the calculated turbulence forecast results.

[0075] exist Figure 2In the embodiment shown, the WRF server downloads the meteorological data of the laser communication station at the first moment, and extracts multiple meteorological factors after preprocessing the meteorological data. Each meteorological factor is automatically reported to the preliminary calculation unit at regular intervals. That is, the atmospheric refractive index structure constant corresponding to each meteorological factor is calculated by the first formula corresponding to the target model. Then, the environmental characteristics corresponding to the laser communication station are obtained to update the turbulence profile, and a new turbulence profile is obtained. Then, the atmospheric refractive index structure constant is integrated according to the new flow profile to obtain the turbulence forecast result corresponding to the meteorological data.

[0076] The atmospheric optical turbulence forecasting method provided by this invention updates the turbulence profile by extracting environmental characteristics of the laser communication station, making the turbulence forecasting model more consistent with the actual situation of the laser communication station site, thereby improving the prediction accuracy of atmospheric coherence length corresponding to meteorological data.

[0077] In this embodiment, the method further includes: receiving satellite orbit information sent by an external system, the satellite orbit information including multiple azimuth elevation angles of the satellite in its orbit, each of the multiple azimuth elevation angles corresponding to different updated turbulence prediction results; obtaining target turbulence prediction results corresponding to the multiple azimuth elevation angles and comprehensive turbulence prediction results corresponding to the satellite orbit based on the satellite orbit information; and sending the target turbulence prediction results corresponding to the multiple azimuth elevation angles and the comprehensive turbulence prediction results to the external system.

[0078] It should be noted that a satellite has multiple azimuth and elevation angles on a single satellite orbit. Different azimuth and elevation angles correspond to different turbulence prediction results, and the entire satellite orbit corresponds to a comprehensive turbulence prediction result. For example, at the perigee, geostationary, or other moving positions on the satellite orbit, the satellite can conduct laser communication with the ground laser communication station at different moving positions. When the ground laser communication station performs a laser communication mission each time, it can receive the corresponding satellite orbit information.

[0079] In this embodiment, the orbital information may include the satellite's position in the orbit and the corresponding travel time, and may also include orbital type information, etc.

[0080] exist Figure 2In the illustrated embodiment, after extracting the time coefficient (corresponding to time characteristics) from the atmospheric coherence length collected in real time by the DIMM and the industrial control computer, both the time coefficient and the turbulence prediction results are reported to the time coefficient processing unit. The time coefficient is used to correct the turbulence prediction results output by the preliminary calculation unit to obtain the prediction results in the vertical direction. The turbulence prediction results and the satellite orbit information corresponding to the laser communication mission sent by the external system are sent to the mission support unit to match the satellite's azimuth and elevation angles with different updated turbulence prediction results. The matching results are then fed back to the external system. Alternatively, the comprehensive judgment results (corresponding to the comprehensive turbulence prediction results) corresponding to the entire satellite orbit can be sent to the external system.

[0081] In this embodiment, the matching result is used to indicate the support of the updated turbulence prediction result for the laser communication task. That is, the matching result can be a comprehensive judgment result based on whether the entire orbit supports laser communication provided by the satellite orbit information, or it can be a comprehensive judgment result of laser communication corresponding to each position on the orbit.

[0082] In some embodiments, the time coefficient is dynamically changed in real time, and its value depends on the atmospheric coherence length results monitored in real time by DIMM.

[0083] The atmospheric optical turbulence prediction method provided by this invention obtains laser communication mission support results related to atmospheric turbulence by matching the updated turbulence prediction results with satellite orbit information, thus providing a basis for the planning of satellite-to-ground laser communication missions.

[0084] In some embodiments, the first formula is:

[0085]

[0086] in, Let be the atmospheric refractive index structure constant, a be a constant, L0 be the turbulent external scale, and M be the potential refractive index gradient.

[0087] In this embodiment, 'a' can be 2.8, and 'M' can be obtained using the following formula:

[0088]

[0089] Where z is altitude in meters (m), P is air pressure, and θ is potential temperature in Kelvin (K). The expression for θ is:

[0090]

[0091] Where T is the current air temperature; the relationship between L0 and the wind shear and temperature gradient at high altitudes is as follows:

[0092]

[0093] Where S is the wind shear, and the expression for S is:

[0094]

[0095] Where u and v represent zonal wind speed and meridional wind speed, respectively, and the unit is m / s.

[0096] In this embodiment, the atmospheric refractive index structure constant corresponding to each meteorological factor in the meteorological parameters can be calculated using the first formula, and the atmospheric refractive index structure constant can be integrated according to the preset turbulence profile to obtain the turbulence forecast result.

[0097] The atmospheric optical turbulence forecasting method provided by this invention calculates the atmospheric refractive index structure constants corresponding to multiple meteorological factors in the first formula, thereby realizing the quantitative representation of turbulence information in meteorological data.

[0098] The atmospheric optical turbulence prediction device provided by the present invention is described below. The atmospheric optical turbulence prediction device described below and the atmospheric optical turbulence prediction method described above can be referred to in correspondence.

[0099] Figure 3 This is one of the structural schematic diagrams of the atmospheric optical turbulence prediction device provided by the present invention, such as... Figure 3 As shown, the atmospheric optical turbulence forecasting device includes: an acquisition module 310, a first processing module 320, and a second processing module 330.

[0100] The acquisition module 310 is used to acquire meteorological data at the first moment and atmospheric coherence length data within the first time period;

[0101] The first processing module 320 is used to input meteorological data into the target model to obtain preliminary turbulence forecast results. The target model is used to predict the turbulence intensity of the meteorological data.

[0102] The second processing module 330 is used to extract the temporal features of the atmospheric coherence length data and update the preliminary turbulence forecast results based on the temporal features to obtain the updated turbulence forecast results. The temporal features are used to represent the amount of change in the atmospheric coherence length data within the target number of days.

[0103] The atmospheric optical turbulence forecasting device provided by this invention calculates the turbulence forecasting results for future times by acquiring meteorological data for future times, and extracts the temporal characteristics of atmospheric coherence length data collected in real time. Then, it uses the temporal characteristics to update the turbulence forecasting results for future times, thereby reducing the interference of errors caused by the dynamic and random nature of turbulence on the turbulence forecasting results and improving the accuracy of atmospheric optical turbulence forecasting.

[0104] In some embodiments, the atmospheric optical turbulence forecasting device further includes: a receiving module for receiving satellite orbit information sent by an external system, the satellite orbit information including multiple azimuth elevation angles of the satellite in its orbit, each of the multiple azimuth elevation angles corresponding to different updated turbulence forecasting results; a third processing module for obtaining target turbulence forecasting results corresponding to the multiple azimuth elevation angles and comprehensive turbulence forecasting results corresponding to the satellite orbit based on the satellite orbit information; and a sending module for sending the target turbulence forecasting results corresponding to the multiple azimuth elevation angles and the comprehensive turbulence forecasting results to the external system.

[0105] The atmospheric optical turbulence prediction device provided by this invention obtains laser communication mission support results related to atmospheric turbulence by matching the updated turbulence prediction results with satellite orbit information, thus providing a basis for the planning of satellite-to-ground laser communication missions.

[0106] In some embodiments, the atmospheric optical turbulence forecasting device further includes an integrated control module and an information storage module, wherein the integrated control module is used to send signal commands and the information storage module is used to store the updated turbulence forecast results.

[0107] Figure 4 This is the second schematic diagram of the atmospheric optical turbulence prediction device provided by the present invention; Figure 4 In the illustrated embodiment, the integrated control module controls the acquisition module to acquire meteorological data at a first moment and atmospheric coherence length data within a first time period. The meteorological data is then processed by the first processing module to obtain turbulence forecast data. The turbulence forecast data is then updated by the second processing module to obtain updated turbulence forecast data. The updated turbulence forecast data is then sent to the information storage module for storage. After receiving satellite orbit information sent by the external system, the integrated control module calls the updated turbulence forecast data in the information storage module for matching. Finally, the matching result is fed back to the external system.

[0108] The atmospheric optical turbulence forecasting device provided by this invention, by setting up an integrated control server and an information storage module, enables the atmospheric optical turbulence forecasting device to have the ability to monitor equipment, acquire data, store data, process data, and interact with external systems, thereby improving the efficiency of atmospheric optical turbulence forecasting.

[0109] Figure 5 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 5As shown, the electronic device may include a processor 510, a communication interface 520, a memory 530, and a communication bus 540. The processor 510, communication interface 520, and memory 530 communicate with each other via the communication bus 540. The processor 510 can call logical instructions in the memory 530 to execute an atmospheric optical turbulence forecasting method. This method includes: acquiring meteorological data at a first moment and atmospheric coherence length data within a first time period; inputting the meteorological data into a target model to obtain preliminary turbulence forecast results, the target model being used to predict the turbulence intensity of the meteorological data; extracting the temporal characteristics of the atmospheric coherence length data, and updating the preliminary turbulence forecast results based on the temporal characteristics to obtain updated turbulence forecast results, the temporal characteristics representing the change in atmospheric coherence length data within a target number of days.

[0110] Furthermore, the logical instructions in the aforementioned memory 530 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0111] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the atmospheric optical turbulence forecasting method provided by the above methods. The method includes: acquiring meteorological data at a first moment and atmospheric coherence length data within a first time period; inputting the meteorological data into a target model to obtain a preliminary turbulence forecast result, wherein the target model is used to predict the turbulence intensity of the meteorological data; extracting the temporal features of the atmospheric coherence length data and updating the preliminary turbulence forecast result based on the temporal features to obtain an updated turbulence forecast result, wherein the temporal features are used to represent the change in atmospheric coherence length data within a target number of days.

[0112] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the atmospheric optical turbulence forecasting method provided by the above methods. The method includes: acquiring meteorological data at a first moment and atmospheric coherence length data within a first time period; inputting the meteorological data into a target model to obtain a preliminary turbulence forecast result, wherein the target model is used to predict the turbulence intensity of the meteorological data; extracting the temporal features of the atmospheric coherence length data, and updating the preliminary turbulence forecast result based on the temporal features to obtain an updated turbulence forecast result, wherein the temporal features are used to represent the amount of change of the atmospheric coherence length data within a target number of days.

[0113] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0114] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0115] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method of atmospheric optical turbulence prediction, characterized in that, The method comprises: obtaining meteorological data at a first time and atmospheric coherence length data within a first time period; inputting the meteorological data into a target model to obtain a preliminary turbulence prediction result, the target model being used to predict the turbulence intensity of the meteorological data; extracting a time feature of the atmospheric coherence length data, and updating the preliminary turbulence prediction result based on the time feature to obtain an updated turbulence prediction result, the time feature being used to represent the variation of the atmospheric coherence length data within a target number of days; the meteorological data comprises a plurality of meteorological factors, and the target model comprises a first formula and a turbulence profile, the turbulence profile being used to represent the variation characteristics of turbulence with height, and the inputting of the meteorological data into the target model to obtain the preliminary turbulence prediction result comprises: obtaining atmospheric refractive index structure constants corresponding to the plurality of meteorological factors at different layer heights based on the first formula; integrating the atmospheric refractive index structure constants corresponding to the plurality of meteorological factors at different layer heights according to the turbulence profile to obtain the preliminary turbulence prediction result; the meteorological data comprises a plurality of meteorological factors, and the target model comprises a first formula and a turbulence profile, the turbulence profile being used to represent the variation characteristics of turbulence with height, and the inputting of the meteorological data into the target model to obtain the preliminary turbulence prediction result further comprises: obtaining target atmospheric coherence length data based on a difference image motion monitoring device; extracting environmental features and time sequence variation features from the target atmospheric coherence length data, and updating the turbulence profile based on the environmental features and the time sequence variation features; integrating the atmospheric refractive index structure constants corresponding to the plurality of meteorological factors at different layer heights according to the updated turbulence profile to obtain the turbulence prediction result, the atmospheric refractive index structure constants being obtained based on the first formula.

2. The method of atmospheric optical turbulence forecasting according to claim 1, wherein, The method further comprises: receiving satellite orbit information sent by an external system, the satellite orbit information comprising a plurality of azimuth-elevation angles of a satellite on an orbit, the plurality of azimuth-elevation angles respectively corresponding to different updated turbulence prediction results; obtaining target turbulence prediction results corresponding to the plurality of azimuth-elevation angles and a comprehensive turbulence prediction result corresponding to the satellite orbit based on the satellite orbit information; sending the target turbulence prediction results corresponding to the plurality of azimuth-elevation angles and the comprehensive turbulence prediction result to the external system.

3. The method of atmospheric optical turbulence forecasting according to claim 1, wherein, The first formula is: wherein, is the atmospheric refractive index structure constant, a is a constant, L0is the outer scale of turbulence, and M is the potential refractive index gradient.

4. An atmospheric optical turbulence prediction device using the atmospheric optical turbulence prediction method according to claim 1, characterized by The method comprises: an obtaining module, configured to obtain meteorological data at a first time and atmospheric coherence length data within a first time period; a first processing module, configured to input the meteorological data into a target model to obtain a preliminary turbulence prediction result, the target model being used to predict the turbulence intensity of the meteorological data; a second processing module, configured to extract a time feature of the atmospheric coherence length data, and update the preliminary turbulence prediction result based on the time feature to obtain an updated turbulence prediction result, the time feature being used to represent the variation of the atmospheric coherence length data within a target number of days.

5. The device for predicting optical turbulence of the atmosphere according to claim 4, characterized in that, The device further comprises: receive satellite orbit information sent by an external system, the satellite orbit information comprising a plurality of azimuth-elevation angles of a satellite in an orbit, the plurality of azimuth-elevation angles respectively corresponding to different updated turbulence prediction results; a third processing module, configured to obtain target turbulence prediction results corresponding to the plurality of azimuth-elevation angles and a comprehensive turbulence prediction result corresponding to the satellite orbit based on the satellite orbit information; a sending module, configured to send the target turbulence prediction results corresponding to the plurality of azimuth-elevation angles and the comprehensive turbulence prediction result to the external system.

6. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor implements the atmospheric optical turbulence prediction method according to any one of claims 1 to 3 when executing the program.

7. A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program, when executed by the processor, implements the atmospheric optical turbulence prediction method according to any one of claims 1 to 3.

8. A computer program product comprising a computer program, characterized in that, The computer program, when executed by the processor, implements the atmospheric optical turbulence prediction method according to any one of claims 1 to 3.

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